"author:johannschiffer" matching MCP servers:

Enables AI coding agents to discover installed host compilers, execute builds in isolated child environments with timeout enforcement, and convert noisy ANSI-laden compiler logs from Python, Rust, C/C++, Node, and Go toolchains into clean structured JSON diagnostics. It also reports toolchain readiness so agents can avoid blind invocations of missing compilers.

Enables AI agents to fetch web pages, convert them into token-efficient semantic Markdown, and extract hyperlinks and page metadata while rotating realistic browser fingerprints to reduce anti-bot blocks.

Gives AI agents safe, bounded, non-blocking access to Linux sysadmin inspection tasks, including CPU, RAM and disk healthchecks, memory-safe log tailing with regex filtering, and user-level systemd service and timer auditing. All operations run without sudo or unrestricted root shells, avoiding interactive pager hangs and context window flooding.

A lightweight MCP server that lets AI agents send real-time alerts, operational notifications, and webhook messages through Telegram bots and Discord webhooks without exposing primary API keys or relying on heavy middleware. It provides tools for delivering Markdown-formatted Telegram messages and rich Discord embed cards, plus a channel status/health check.

Enables AI coding assistants to analyze DDL migration scripts before execution, flagging table-locking, destructive, and backward-incompatible changes, estimating lock duration and risk, and inspecting schema diffs through MCP tools.

Enables AI agents to navigate headless web pages, extract token-efficient accessibility trees and clean text, and interact with elements via stable node identifiers. It reduces context usage by converting pages into compact AOM structures and supports clicking, form filling, and page status checks.

Enables multiple AI agents to coordinate in parallel by atomically claiming tasks and transitioning their state, preventing collisions, zombie locks, and duplicated work without external dependencies.

Enables AI agents to inspect database schemas and run strictly read-only SQL queries with guardrails against destructive statements, multi-statement chaining, and unbounded scans. Supports SQLite natively and PostgreSQL optionally.

Enables AI agents to safely manage GitHub issues, inspect discussions, create pull requests, and audit GitHub Actions CI status through strict branch-protection guards.

Enables autonomous AI coding agents to claim exclusive per-domain execution seats, record session handover notes, and validate terminal commands against domain whitelists to prevent concurrency collisions, context loss, and out-of-domain actions.

The server enables AI agents to define and execute predictable, multi-step data pipelines using a declarative workflow graph. It guarantees deterministic execution order and provides visual representations of the data flow without relying on heavy cloud orchestrators.

Enables Python developers to define MCP tools via decorators, auto-generate schemas and tests, and package compliant MCP servers with CLI scaffolding and JSON-RPC 2.0 stdio transport.

Enables AI agents to generate structured PRDs, decompose epics into testable user stories, validate Given/When/Then acceptance criteria, and export markdown backlogs.

Enables AI coding agents to run sub-millisecond, fully offline CVE lookups and audit dependency manifests such as requirements.txt and package.json against known vulnerable version ranges. It returns CVSS severity details and calculates the minimal safe upgrade version needed to eliminate matching vulnerabilities, without rate limits or API keys.

Enables AI browser agents to classify static assets and route each request to direct, datacenter, or residential proxy tiers so heavy media and fonts avoid expensive paid bandwidth. It also generates rotating modern browser evasion headers and reports real-time megabyte and dollar savings from the traffic diverted.